Kafka to Red Ant: A Strange Metamorphosis

Before I make a start I would want to make it very clear that inspite of what that the title may suggest, this is not a “sensational” post. It is just something that really intrigued me. It basically falls under the domain of image segmentation and pattern recognition, however it is something that can intrigue a person with a non-scientific background with a like (or dislike) for Franz Kafka’s work equally. I keep the title because it is the title of an original work by Dr Vitorino Ramos and hence making changes to it is not a good thing.

Note: For people who are  not interested in technical details can skip those parts and only read the stuff in bold there.

Franz Kafka is one writer whose works have had a profound impact on me in terms that they disturbed me each time I thought about them. No, not because of his writings per se ONLY but for a greater part because i had read a lot on his rather tragic life and i saw a heart breaking reflection in his works of what happened in his life (i see a lot of similarities between Kafka’s life and that of Premchand albeit that Premchand’s work got published in his lifetime mostly, though he got true critical acclaim after his death). Yes i do think that his writings give a good picture of Europe at that time, on human needs and behavior, but the prior reason outweighs all these. Kafka remains one of my favorite writers, though his works are basically short stories. He mostly wrote on a theme that emphasized the alienation of man and the indifferent society. Kafka’s tormenting thoughts on dehumanization, the cruel world, bureaucratic labyrinths which he experienced as being part of the not so liked Jewish minority in Prague, his experiences in jobs he did, his love life and affairs, on a constant fear of mental and physical collapse as a result of clinical depression and the ill health that he suffered from, reflected in a lot of his works. Including in his novella The Metamorphosis.

W. H Auden rightly wrote about Kafka:

“Kafka is important to us because his predicament is the predicament of the modern man”

In metamorphosis the protagonist Gregor Samsa turns into a giant insect when he wakes up one morning. It is kind of apparent that the “transformation” was meant in a metaphorical sense by Kafka and not in a literal one, mostly based on his fears and his own life experiences. The Novella starts like this. . .

As Gregor Samsa awoke one morning from uneasy dreams he found himself transformed in his bed into a monstrous vermin.

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While rummaging through a few scientific papers that explored the problem of pattern recognition using a distributed approach i came across a few by Dr Ramos et al, which dealt with the issue using the artificial colonies approach.

In the previous post i had mentioned that the self organization of neurons into a brain like structure and the self organization of an ant colony were similar in more than a few ways. If it may be implemented then it could have implications in pattern recognition problems, where the perceptive abilities emerge from the local and simple interactions of simple agents. Such decentralized systems, a part of the swarm intelligence paradigm look very promising in applying to pattern recognition and the specific case of image segmentation as basically these may be considered a clustering and combinatorial problem taking the image itself as an ant colony habit.

The basis for this post was laid down in the previous post on colony cognitive maps. We observed the evolution of a pheromonal field there and a simple model for the same:

[Evolution of a distribution of (artificial) ants over time: Image Source]

Click to Enlarge

The above is the evolution of the distribution of artificial ants in a square lattice, this work has been extended to digital image lattices by Ramos et al. Image segmentation is an image processing problem wherein the regions of the image under consideration may be partitioned into different regions. Like into areas of low contrast and areas of high contrast, on basis of texture and grey level and so on. Image segmentation is very important as the output of an image segmentation process may be used as an input in object recognition based scenarios. The work of Ramos et al (In references below) and some of the papers cited in his works have really intrigued me and i would strongly suggest readers to have a look at them if at all they are interested in image segmentation, pattern recognition and self organization in general, some might also be interested in implementing something similar too!

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In one of the papers a swarm of artificial ants was thrown on a digital habitat (an image of Albert Einstein) to explore it for 1000 iterations. The Einstein image is replaced by a map image. The evolution of the colony cognitive maps for the Einstein image habitat is shown below for various iterations.

[Evolution of a pheromonal field on an Einstein image habitat for t= 0, 1, 100, 110, 120, 130, 150, 200, 300, 400, 500, 800, 900, 1000: Image Source]

The above is represented most aptly in a .gif image.

[Evolution of a pheromonal field on an Einstein habitat: Image Source]

Now instead of Einstein a Kafka image was taken and was subject to the same. Image Source

The Kafka image habitat is replaced by a red ant in the second row. The abstract of the paper by the same name goes as.

Created with an Artificial Ant Colony, that uses images as Habitats, being sensible to their gray levels. At the second row,  Kafka is replaced as a substrate, by Red Ant. In black, the higher levels of pheromone (a chemical evaporative sugar substance used by swarms on their orientation trough out the trails). It’s exactly this artificial evaporation and the computational ant collective group synergy reallocating their upgrades of pheromone at interesting places, that allows for the emergence of adaptation and “perception” of new images. Only some of the 6000 iterations processed are represented. The system does not have any type of hierarchy, and ants communicate only in indirect forms, through out the successive alteration that they found on the Habitat.

Now what intrigues me is that the transition is extremely rapid. Such perceptive ability with change in the image habitat could have massive implications at how we look at pattern recognition for such cases.

Extremely intriguing!

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Resources on Franz Kafka:

1. A Brief Biography

2. The Metamorphosis At Project Gutenberg. Click here >>

3. The Kafka Project

References and STRONGLY recommended papers:

1. Artificial Ant Colonies in Digital Image Habitats – A Mass behavior Effect Study on Pattern Recognition. Vitorino Ramos and Filipe Almeida. Click Here >>

2. Social Cognitive Maps, Swarms Collective Perception and Distributed Search on Dynamic Landscapes. Vitorino Ramos, Carlos Fernandes, Agostinho C. Rosa. Click Here >>

3. Self-Regulated Artificial Ant Colonies on Digital Image Habitats. Carlos Fernandes, Vitorino Ramos, Agostinho C. Rosa. Click Here >>

4. On the Implicit and the Artificial – Morphogenesis and Emergent Aesthetics in Autonomous Collective Systems. Vitorino Ramos. Click Here >>

5. A Strange Metamorphosis [Kafka to Red Ant], Vitorino Ramos.

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Colony Cognitive Maps

Some posts back, i posted on Non-Human Art or Swarm Paintings, there I mentioned that those paintings were NOT random but were a Colony Cognitive Map.

This post will serve as the conceptual basis for the Swarm Paintings post, the next post and a few future posts on image segmentation.

Motivation: Some might wonder what is the point of writing about such a topic. And that it is totally unrelated to what i write about generally. No! That is not the case. Most of the stuff I write about is related in some sense. Well the motivation for reading thoroughly about this (and writing) maybe condensed into the following:

1. The idea of a colony cognitive map is used in SI/A-life experiments, areas that really interest me.

2. Understanding the idea of colony cognitive maps gives a much better understanding of the inherent self organization in insect swarms and gives a lead to understand self organization in general.

3. The parallel to colony cognitive maps, the cognitive maps follow from cognitive science and brain science. Again areas that really interest me as they hold the key for the REAL artificial intelligence evolution and development in the future.

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The term “Colony Cognitive Map” as i had pointed earlier is in a way a parallel to a Cognitive Map in brain science (i use the term brain science for a combination of fields like neuroscience, Behavioral psychology, cognitive sciences and the likes and will use it in this meaning in this post ) and also that the name is inspired from the same!

There is more than just a romantic resemblance between the self-organization of “simple” neurons into an intelligent brain like structure, producing behaviors well beyond the capabilities of an individual neuron and the self-organization of simple and un-intelligent insects into complex swarms and producing intelligent and very complex and also aesthetically pleasing behavior! I have written previously on such intelligent mass behavior. Consider another example, neurons are known to transmit neurotransmitters in the same way a social insect colony is marked by pheromone deposition and laying.

[Self Organization in Neurons (Left) and a bird swarm(Below).  Photo Credit >> Here and Here]

First let us try to revisit what swarm intelligence roughly is (yes i still am to write a post on a mathematical definition of the same!), Swarm Intelligence is basically a property of a system where the collective actions of unsophisticated agents, acting locally causes functional and sophisticated global patterns to emerge. Swarm intelligence gives a scheme to explore decentralized problem solving. An example that is also one of my favorites is that of a bird swarm, wherein the collective behaviors of birds each of which is very simple causes very complex global patterns to emerge. Over which I have written previously, don’t forget to look at the beautiful video there if you have not done so already!

Self Organization in the Brain: Over the last two months or so i had been reading Douglas Hofstadter’s magnum opus, Gödel, Escher, Bach: an Eternal Golden Braid (GEB). This great book makes a reference to the self organization in the brain and its comparison with the behavior of the ant colonies and the self organization in them as early as 1979.

[Photo Source: Wikipedia Commons]

A brain is often regarded as one of the most if not the most complex entity. However if we look at a rock it is very complex too, but then what makes a brain so special? What distinguishes the brain from something like a rock is the purposeful arrangement of all the elements in it. The massive parallelism and self organization that is observed in it too amongst other things makes it special. Research in Cybernetics in the 1950s and 1960s lead the “cyberneticians” to try to explain the complex reactions and actions of the brain without any external instruction in terms of self organization. Out of these investigations the idea of neural networks grew out (1943 – ), which are basically very simplified models of how neurons interact in our brains. Unlike the conventional approaches in AI there is no centralized control over a neural network. All the neurons are connected to each other in some way or the other but just like the case in an ant colony none is in control. However together they make possible very complex behaviors. Each neuron works on a simple principle. And combinations of many neurons can lead to complex behavior, an example believed to be due to self-organization. In order to help the animal survive in the environment the brain should be in tune with it too. One way the brain does it is by constantly learning and making predictions on that basis. Which means a constant change and evolution of connections.

Cognitive Maps: The concept of space and how humans perceive it has been a topic that has undergone a lot of discussion in academia and philosophy. A cognitive map is often called a mental map, a mind map, cognitive model etc.

The origin of the term Cognitive Map is largely attributed to Edward Chace Tolman, here cognition refers to mental models that people use to perceive, understand and react to seemingly complex information. To understand what a mental model means it would be favorable to consider an example I came across on wikipedia on the same. A mental model is an inherent explanation in somebody’s thought process on how something works in the spatial or external world in general. It is hypothesized that once a mental model for something or some representation is formed in the brain it can replace careful analysis and careful decision making to reduce the cognitive load. Coming back to the example consider a mental model in a person of perceiving the snake as dangerous. A person who holds this model will likely rapidly retreat as if is like a reflex without initial conscious logical analysis. And somebody who does not hold such a model might not react in the same way.

Extending this idea we can look at cognitive maps as a method to structure, organize and store spatial information in the brain which can reduce the cognitive load using mental models and and enhance quick learning and recall of information.

In a new locality for example, human way-finding involves recognition and appreciation of common representations of information such as maps, signs and images so to say. The human brain tries to integrate and connect this information into a representation which is consistent with the environment and is a sort of a “map”. Such spatial (not necessarily spatial) internal representations formed in the brain can be called a cognitive map. As the familiarity of a person with an area increases then the reliance on these external representations of information gradually reduces. And the common landmarks become a tool to localize within a cognitive map.

Cognitive maps store conscious perceptions of the sense of position and direction and also the subconscious automatic interconnections formed as a result of acquiring spatial information while traveling through the environment. Thus they (cognitive maps) help to determine the position of a person, the positioning of objects and places and the idea of how to get from one place unto another. Thus a cognitive map may also be said to be an internal cognitive collage.

Though metaphorically similar the idea of a cognitive map is not really similar to a cartographic map.

Colony Cognitive Maps: With the above general background it would be much easier to think of a colony cognitive map. As it is basically a analogy to the above. As described in my post on adaptive routing, social insects such as ants construct trails and networks of regular traffic via a process of pheromone deposition, positive feedback and amplification by the trail following. These are very similar to cognitive maps. However one obvious difference lies in the fact that cognitive maps lie inside the brain and social insects such as ants write their spatial memories in the external environment.

Let us try to picture this in terms of ants, i HAVE written about how a colony cognitive map is formed in this post without mentioning the term.

A rather indispensable aspect of such mass communication as in insect swarms is Stigmergy. Stigmergy refers to communication indirectly, by using markers such as pheromones in ants. Two distinct types of stigmergy are observed. One is called sematectonic stigmergy, it involves a change in the physical environment characteristics.An example of sematectonic stigmergy is nest building wherein an ant observes a structure developing and adds its ball of mud to the top of it. Another form of stigmergy is sign-based and hence indirect. Here something is deposited in the environment that makes no direct contribution to the task being undertaken but is used to influence the subsequent behavior that is task related. Sign based stigmergy is very highly developed in ants. Ants use chemicals called as pheromones to develop a very sophisticated signaling system. Ants foraging for food lay down some pheromone which marks the path that they follow. An isolated ant moves at random but an ant encountering a previously laid trail will detect it and decide to follow it with a high probability and thereby reinforce it with a further quantity of pheromone. Since the pheromone will evaporate the lesser used paths will gradually vanish. We see that this is a collective behavior.

Now we assume that in an environment the actors (say for example ants) emit pheromone at a set rate. Also there is a constant rate at which the pheromone evaporates. We also assume that the ants themselves have no memory of previous paths taken and act ONLY on the basis of the local interactions with pheromone concentrations in the vicinity. Now if we consider the “field” or “map” that is the overall result and formed in the environment as a result of the movements of the individual ants over a fixed period of time. Then this “pheromonal” field contains information about past movements and decisions of the individual ants.

The pheromonal field (cognitive map) as i just mentioned contains information about past movements and decisions of the organisms, but not arbitrarily far in the past since the field “forgets” its distant history due to evaporation in time. Now this is exactly a parallel to a cognitive map, with the difference that for a colony the spatial information is written in the environment unlike inside the brain in the case of a human cognitive map. Another major similarity is that neurons release a number of neurotransmitters which can be considered to  be a parallel to the pheromones released as described above! The similarities are striking!

Now if i look back at the post on swarm paintings, then we can see that the we can make such paintings, with the help of a swarm of robots. More pheromone concentration on a path means more paint. And hence the painting is NOT random but is EMERGENT. I hope i could make the idea clear.

How Swarms Build Colony Cognitive Maps: Now it would be worthwhile to look at a simple model of how ants construct cognitive maps, that I read about in a wonderful paper by Mark Millonas and Dante Chialvo. Though i have already mentioned, I’ll still sum up the basic assumptions.

Assumptions:

1. The individual agent (or ant) is memoryless.

2. There is no direct communication between the organisms.

3. There is no spatial diffusion of the pheromone deposited. It remains fixed at a point where it was deposited.

4. Each agent emits pheromone at a constant rate say .

Stochastic Transition Probabilities:

Now the state of each agent can be described by a phase variable which contains its position and orientation . Since the response at any given time is dependent solely on the present and not the previous history, it would be sufficient to specify the transition probability from one location to another place and orientation an instant later. Thus the movement of each individual agent can be considered roughly to be a continuous markov process whose probabilities at each and every instance of time are decided by the pheromone concentration .

By using theoretical considerations, generalizations from observations in ant colonies the response function can be effectively summed up into a two parameter pheromone weight function.

This weight function measures the relative probabilities in moving to a site with the pheromone density .

Another parameter may be considered. This parameter measures the degree of randomness by which an agent can follow a pheromone trail. For low values of the pheromone concentration does not largely impact its choice but higher values do.

At this point we can define another factor . This signifies the sensory capability. It describes the fact that the ants ability to sense pheromone decreases somewhat at higher concentrations. Something like a saturation scenario.

Pheromone Evolution: It is essential to describe how the pheromone evolves. According to an assumption already made, each agent emits pheromone at a constant rate with no spatial diffusion. If the pheromone at a location is not replenished then it will gradually evaporate. The pheromonal field so formed does contain a memory of the past movements of the agents in space, however because of the evaporation process it does not have a very distant memory.

Analysis: Another important parameter is the regarding the number of ants present, the density of ants . Thus using all these parameters we can define a single parameter, the average pheromonal field . Where is what i mentioned above, the rate of scent decay.

Further detailed analysis can be studied out here. With the above background it is just a matter of understanding.

[Evolution of distribution of ants : Source]

Click to Enlarge

Now after continuing with the mathematical analysis in the hyperlink above, we fix the values of the parameters.

Then a large number of ants are placed at random positions, the movement of each ant is determined by the probability .

Another assumption is that the pheromone density at each point at is zero. Each ant deposits pheromone at a decided rate and also the pheromone evaporates at a fixed rate .

In the above beautiful picture we the evolution of a distribution of ants on a 32×32 lattice. A pattern begins to emerge as early as the 100th time step. Weak pheromonal paths are completely evaporated and we finally get a emergent ant distribution pattern as shown in the final image.

The Conclusion that Chialvo and Millonas note is that scent following of the very fundamental type described above (assumptions) is sufficient to produce an evolution (emergence) of complex pattern of organized flow of social insect traffic all by itself. Detailed conclusion can be read in this wonderful paper!

References and Suggested for Further Reading:

1. Cognitive Maps, click here >>

2. Remembrance of places past: A History of Theories of Space. click here >>

3. The Science of Self Organization and Adaptivity, Francis Heylighen, Free University of Brussels, Belgium. Click here >>

4.   The Hippocampus as a Cognitive Map, John O’ Keefe and Lynn Nadel, Clarendon Press, Oxford. To access the pdf version of this book click here >>

5. The Self-Organization in the Brain, Christoph von der Malsburg, Depts for Computer Science, Biology and Physics, University of Southern California.

5. How Swarms Build Cognitive Maps, Dante R. Chialvo and Mark M. Millonas, The Santa Fe Institute of Complexity. Click here >>

6. Social Cognitive Maps, Swarm Collective Perception and Distributed Search on Dynamic Landscapes, Vitorino Ramos, Carlos Fernandes, Agostinho C. Rosa.

Related Posts:

1. Swarm Paintings: Non-Human Art

2. The Working of a Bird Swarm

3. Adaptive Routing taking Cues from Stigmergy in Ants

Possibly Related:

Gödel, Escher, Bach: A Mental Space Odyssey

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The Need For Heretics in the Society

[Photo Source : NASA]

Freeman Dyson is a professor emeritus of Physics at the Institute of Advanced Study at Princeton. Prof Freeman has always been one of my heroes and i regard him as one of the coolest physicists alive today.  I was introduced to him and his work through “What Do You Care What Other People Think” by Richard Feynman years ago.

He thinks ahead of the present generation and is also conspicuously agnostic which i dare say goes against the mainstream in science today, where being politically correct is one problem. These two things lead to very contrasting views on the man. Many in the scientific community, mostly due to the latter thing about him refer to him as a dreamer and many others portray him as a dreamer mad scientist for ideas such Dyson Spheres, Dyson Trees etc, ideas that are too fantastic for most people to digest.

Dyson had also been involved in the fantastic idea of the Project Orion, on which i have dedicated quite a few previous posts. Again many regard the idea of using nuclear fuel to power space ships as absurd, but i have always believed that it is a wonderful idea and i have also tried to write why. Many people think that Dyson has only been involved in such fantasy science, however one must note that he has made many important contributions to quantum physics and mathematics also or “mainstream science”, I have always believed that Freeman Dyson deserved the Nobel prize for QED along with his fellow researchers, he probably missed out due to the three limit on the number of people getting the prize at once. During a discussion with Robert Bradbury, he wholeheartedly agreed with my thinking! A quick search on Google scholar for him indicates about 1600 publications that have his name on the main text. And one must remember that Dyson never took a PhD, probably the only only one to reach IAS without one. Though i am not sure about that.

Below is an excerpt from an essay by Dyson that discusses the need for heretics or people thinking “out of the box” and how the progress in the society is based on such thinking, even if it is utterly and totally wrong! This essay is a little old, but i decided to post it anyway!

The excerpt is originally from his book: A Many-Colored Glass – Reflections on the place of life in the Universe. A second source is here.

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In the modern world, science and society often interact in a perverse way. We live in a technological society, and technology causes political problems. The politicians and the public expect science to provide answers to the problems. Scientific experts are paid and encouraged to provide answers. The public does not have much use for a scientist who says, “Sorry, but we don’t know”. The public prefers to listen to scientists who give confident answers to questions and make confident predictions of what will happen as a result of human activities. So it happens that the experts who talk publicly about politically contentious questions tend to speak more clearly than they think. They make confident predictions about the future, and end up believing their own predictions. Their predictions become dogmas which they do not question. The public is led to believe that the fashionable scientific dogmas are true, and it may sometimes happen that they are wrong. That is why heretics who question the dogmas are needed.

As a scientist I do not have much faith in predictions. Science is organized unpredictability. The best scientists like to arrange things in an experiment to be as unpredictable as possible, and then they do the experiment to see what will happen. You might say that if something is predictable then it is not science. When I make predictions, I am not speaking as a scientist. I am speaking as a story-teller, and my predictions are science-fiction rather than science. The predictions of science-fiction writers are notoriously inaccurate. Their purpose is to imagine what might happen rather than to describe what will happen. I will be telling stories that challenge the prevailing dogmas of today. The prevailing dogmas may be right, but they still need to be challenged. I am proud to be a heretic. The world always needs heretics to challenge the prevailing orthodoxies. Since I am heretic, I am accustomed to being in the minority. If I could persuade everyone to agree with me, I would not be a heretic.

We are lucky that we can be heretics today without any danger of being burned at the stake. But unfortunately I am an old heretic. Old heretics do not cut much ice. When you hear an old heretic talking, you can always say, “Too bad he has lost his marbles”, and pass on. What the world needs is young heretics. I am hoping that one or two of the people who read this piece may fill that role.

Two years ago, I was at Cornell University celebrating the life of Tommy Gold, a famous astronomer who died at a ripe old age. He was famous as a heretic, promoting unpopular ideas that usually turned out to be right. Long ago I was a guinea-pig in Tommy’s experiments on human hearing. He had a heretical idea that the human ear discriminates pitch by means of a set of tuned resonators with active electromechanical feedback. He published a paper explaining how the ear must work, [Gold, 1948]. He described how the vibrations of the inner ear must be converted into electrical signals which feed back into the mechanical motion, reinforcing the vibrations and increasing the sharpness of the resonance. The experts in auditory physiology ignored his work because he did not have a degree in physiology. Many years later, the experts discovered the two kinds of hair-cells in the inner ear that actually do the feedback as Tommy had predicted, one kind of hair-cell acting as electrical sensors and the other kind acting as mechanical drivers. It took the experts forty years to admit that he was right. Of course, I knew that he was right, because I had helped him do the experiments.

Later in his life, Tommy Gold promoted another heretical idea, that the oil and natural gas in the ground come up from deep in the mantle of the earth and have nothing to do with biology. Again the experts are sure that he is wrong, and he did not live long enough to change their minds. Just a few weeks before he died, some chemists at the Carnegie Institution in Washington did a beautiful experiment in a diamond anvil cell, [Scott et al., 2004]. They mixed together tiny quantities of three things that we know exist in the mantle of the earth, and observed them at the pressure and temperature appropriate to the mantle about two hundred kilometers down. The three things were calcium carbonate which is sedimentary rock, iron oxide which is a component of igneous rock, and water. These three things are certainly present when a slab of subducted ocean floor descends from a deep ocean trench into the mantle. The experiment showed that they react quickly to produce lots of methane, which is natural gas. Knowing the result of the experiment, we can be sure that big quantities of natural gas exist in the mantle two hundred kilometers down. We do not know how much of this natural gas pushes its way up through cracks and channels in the overlying rock to form the shallow reservoirs of natural gas that we are now burning. If the gas moves up rapidly enough, it will arrive intact in the cooler regions where the reservoirs are found. If it moves too slowly through the hot region, the methane may be reconverted to carbonate rock and water. The Carnegie Institute experiment shows that there is at least a possibility that Tommy Gold was right and the natural gas reservoirs are fed from deep below. The chemists sent an E-mail to Tommy Gold to tell him their result, and got back a message that he had died three days earlier. Now that he is dead, we need more heretics to take his place.

Thought provoking indeed!

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The Feynman Principle

After the war Feynman joined Hans Bethe at Cornell University. He turned down the offer of a job at The Institute of Advanced Study at Princeton.

“Oh they expected me to be wonderful for they had offered me a job like this. And i wasn’t wonderful. And therefore i realised and made a new principle – I am not responsible for what other people THINK i am able to do. I don’t have to be good because they think i am going to be good. And somehow i could relax about it and think about it that i have not done anything important, oh i am never going to do anything important. I just used to enjoy my work. I used to play with it. I decided that i will do things only for the fun of it…. “

Typed after listening to ” The Pleasure of Finding Things Out”.

The Pleasure of Finding Things Out is one of the most inspiring documentaries that i have seen, However I particularly like this paragraph. Mostly due to personal reasons and experiences!

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The Most Beautiful Thing

Quoting arguably the most influential physicist Albert Einstein.

The most beautiful thing that we can experience is the mysterious, it is the source of all true science and art.

This happens to be one of my favorite quotes. Albert Einstein is one of the few iconic scientists who left us gems on almost every aspect of life. I sometimes refer to him as the easy language Nietzsche in awe of the amount of wisdom packed in just a solitary sentence.

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